5 présentations

• 
  10h30 - 10h55

  Aerial Fleet Planning Using Simulation Models To Improve Inter-Hospital Transfer

  • Joëlle Cormier, prés., HEC Montréal

  This project focuses on strategic decisions, which include the composition of the aircraft fleet, the number of aircraft and the location of the hangars. Real data input and simulation modeling were used to improve the fleet of fixed-wing aircraft in the Canadian province of Québec. This study made it possible to develop a methodology to assess the various trade-offs at the strategic level. Discrete-event simulation is a tool adapted to this problem since it is obviously not possible to carry out tests with real aircraft. Simulation also incorporates the variability present in this type of transfer, such as meteorological events, and mechanical break. It also sheds light on the key trade-offs in the strategic and operational functioning of an aeromedical evacuation service, such as aircraft speed, capacity and accessibility. The close collaboration with the Ministry of Health and Social Services of Quebec allowed to build the model on real data and to offer recommendations specific to the territory and demand for the Canadian province of Quebec. The methodology could be used for different regions around the world or for other types of aerial evacuations.
• 
  10h55 - 11h20

  Guiding Physicians with Time-dependent Patient Selection Policies

  • Mahdi Shakeri, prés.,

  Physicians in emergency departments (EDs) have their own discretion to select the next patient to be seen. Since they operate under an increased workload, such personalized decisions may lead to practices that are less than optimal from a resource utilization perspective and can negatively impact operational and clinical outcomes. In this work, we derive patient selection strategies to guide ED physicians. This is a complex decision and requires the consideration of several factors such as patients’ severity scores, wait times, and the presence of returning patients. In particular, we present a time-dependent policy where the time remaining in a physician’s shift plays an important role. In particular, any patients who are still under the care of the physician at the end of the shift must be transferred to another physician (i.e., patient hand-offs). This is a practice known to compromise the quality of patient care. We formulate an optimal control problem by considering a cost function that captures patient wait times, their acuity, and patient hand-offs. Numerical experiments demonstrate that our proposed time-dependent patient selection policy significantly reduces patient hand-offs compared to traditional time-independent policies while maintaining comparable waiting times and length-of-stay durations.
• 
  11h20 - 11h45

  First or Second Doses First? Vaccine Allocation Under Limited Supply

  • Chaoyu Zhang, prés., University of Toronto

  How to allocate limited two-dose vaccines, such as mRNA vaccines, between the first vs. second doses provoked a heated public debate during COVID-19 in January 2021. In this paper, we study the optimal vaccine allocation between the first vs. second doses with a constant stream of vaccine supply by formulating it as an optimal control problem under disease transmission to minimize the total number of infections over a planning horizon. Specifically, we extend the SIR model to incorporate the role of vaccines by adding two compartments, i.e., people who have received one dose and those who have received two doses. We demonstrate that the optimal vaccine allocation policy has a bang-bang structure: there exists a threshold on the one-dose vaccine efficacy that is higher than one-half of the two-dose vaccine efficacy, above (resp., below) which choosing the “First Doses First” (FDF) (resp., “Second Doses First” (SDF)) policy is optimal. Using COVID-19vaccination data, we calculate thresholds for different countries in January 2021 to recommend to governments whether to use the FDF or SDF policy. Lastly, we demonstrate that our model can be extended to account for boosters by studying how to allocate limited vaccines between the second and booster shots.
• 
  11h45 - 12h10

  Adaptive Server Behavior to Schedule Deviations and Its Consequences: Evidence from Operating Rooms

  • Yiwen Jin, prés., UBC Sauder School of Business

  We investigate the adaptive adjustments in service speed by surgical and cleaning teams in response to real-time deviations from planned operating room (OR) schedules and the subsequent impacts on surgical quality. Employing a unique surgery dataset with actual and scheduled surgery timestamps, we develop a dynamic panel model and utilize the Arellano-Bond Generalized method of moments (GMM) for identification. We reveal a novel type of adaptive server behavior, contributing to both scheduling and behavioral queueing literature while enhancing the understanding of surgical speed and quality. We find that surgical teams expedite subsequent surgeries by an average of 5.6% when facing one standard deviation (SD) delay, while slowing down by an average of 10.5% when one SD ahead of schedule. Similarly, cleaning teams extend turnover durations by 22.1% on average when one SD ahead of schedule and expedite by 10.3% when behind. Leveraging the deviation from the scheduled start as an instrumental variable, we establish a causal relationship between faster-than-scheduled surgery speedup and reduced surgical quality, evidenced by increased 30-day readmission and reoperation probabilities and vice versa. Our findings offer valuable insights for hospital managers in improving OR scheduling, patient satisfaction, and achieving desired efficiency quality trade-offs.
• 
  12h10 - 12h35

  The Impact of Hospital and Patient Characteristics on Psychiatry Readmissions

  • Hossein Hejazian, prés., Desautels Faculty of Management

  A widely observed phenomenon in operations management is ``practice makes perfect'', which constitutes a positive volume-outcome relationship. The nature of this relationship, however, may change in people-centric environments, such as health systems. We study the operational characteristics of hospitals contributing to the re-admission of psychiatry patients. We utilize a data set of about 15,000 psychiatry patients admitted to 25 hospitals in Quebec, Canada. We use a clustered-error probit model which is corrected by the instrumental variable method to perform a causal analysis. We find that the number of patients admitted to a hospital increases the risk of readmission, whereas this risk reduces with the hospital specializing in certain diagnosis classes. We propose that the hospital length of stay (LOS) mediates the effects of hospital characteristics on the risk of readmission. These relationships are also moderated by patient characteristics. Moreover, we find a nonlinear relationship between LOS and the risk of readmission. We provide evidence on the negative volume-outcome and nonlinear LOS outcome relationships. Our results provide insights for policymakers to manage the burden imposed on the health systems by unplanned readmissions from patients with chronic disorders. Our empirical analysis provides potentially helpful insights for managing the flow of psychiatric patients